Incremental clustering of data stream using real ants behavior

被引：0
|
作者：
Masmoudi, Nesrine [2 ]
Azzag, Hanane [1 ]
Lebbah, Mustapha [1 ]
Bertelle, Cyrille [2 ]
机构：
[1] Univ Paris 13, F-93430 Villetaneuse, France
[2] LITIS Univ Havre, F-76600 Le Havre, France
来源：
2014 SIXTH WORLD CONGRESS ON NATURE AND BIOLOGICALLY INSPIRED COMPUTING (NABIC) | 2014年
关键词：
Data analysis; incremental clustering; collective intelligence;
D O I：
暂无
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
We present in this paper a new biomimetic method nammed CL-AntInc for data incremental clustering. This algorithm uses the behavior of real ants. We deal with the issue of data volume through a clustering heuristic. Dynamic graphs are constructed according to a simulation of colonial odors and pheromone mechanisms. We used numerical databases extracted from the Machine Learning Repository. The experimental results show the effectiveness of the suggested algorithm.
引用
收藏
页码：262 / 268
页数：7
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